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At least 487 records · Page 27

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NASA NTRS1999

Unstructured Grid Euler Method Assessment for Longitudinal and Lateral/Directional Aerodynamic Performance Analysis of the HSR Technology Concept Airplane at Supersonic Cruise Speed

Unstructured grid Euler computations, performed at supersonic cruise speed, are presented for a High Speed Civil Transport (HSCT) configuration, designated as the Technology Concept Airplane (TCA) within the High Speed Research (HSR) Program. The numerical results are obtained for the complete TCA cruise configuration which includes the wing, fuselage, empennage, diverters, and flow through nacelles at M (sub infinity) = 2.4 for a range of angles-of-attack and sideslip. Although all the present computations are performed for the complete TCA configuration, appropriate assumptions derived from the fundamental supersonic aerodynamic principles have been made to extract aerodynamic predictions to complement the experimental data obtained from a 1.675%-scaled truncated (aft fuselage/empennage components removed) TCA model. The validity of the computational results, derived from the latter assumptions, are thoroughly addressed and discussed in detail. The computed surface and off-surface flow characteristics are analyzed and the pressure coefficient contours on the wing lower surface are shown to correlate reasonably well with the available pressure sensitive paint results, particularly, for the complex flow structures around the nacelles. The predicted longitudinal and lateral/directional performance characteristics for the truncated TCA configuration are shown to correlate very well with the corresponding wind-tunnel data across the examined range of angles-of-attack and sideslip. The complementary computational results for the longitudinal and lateral/directional performance characteristics for the complete TCA configuration are also presented along with the aerodynamic effects due to empennage components. Results are also presented to assess the computational method performance, solution sensitivity to grid refinement, and solution convergence characteristics.

Ghaffari, Farhad↗

DOE OSTI2017

Integrated Multi-Scale Data Analytics and Machine Learning for the Distribution Grid and Building-to-Grid Interface

This white paper introduces the application of advanced data analytics to the modernized grid. In particular, we consider the field of machine learning and where it is both useful, and not useful, for the particular field of the distribution grid and buildings interface. While analytics, in general, is a growing field of interest, and often seen as the golden goose in the burgeoning distribution grid industry, its application is often limited by communications infrastructure, or lack of a focused technical application. Overall, the linkage of analytics to purposeful application in the grid space has been limited. In this paper we consider the field of machine learning as a subset of analytical techniques, and discuss its ability and limitations to enable the future distribution grid and the building-to-grid interface. To that end, we also consider the potential for mixing distributed and centralized analytics and the pros and cons of these approaches. Machine learning is a subfield of computer science that studies and constructs algorithms that can learn from data and make predictions and improve forecasts. Incorporation of machine learning in grid monitoring and analysis tools may have the potential to solve data and operational challenges that result from increasing penetration of distributed and behind-the-meter energy resources. There is an exponentially expanding volume of measured data being generated on the distribution grid, which, with appropriate application of analytics, may be transformed into intelligible, actionable information that can be provided to the right actors – such as grid and building operators, at the appropriate time to enhance grid or building resilience, efficiency, and operations against various metrics or goals – such as total carbon reduction or other economic benefit to customers. While some basic analysis into these data streams can provide a wealth of information, computational and human boundaries on performing the analysis are becoming significant, with more data and multi-objective concerns. Efficient applications of analysis and the machine learning field are being considered in the loop.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1999

Unstructured Grid Euler Method Assessment for Longitudinal and Lateral/Directional Stability Analysis of the HSR Reference H Configuration at Transonic Speeds

Transonic Euler computations, based on unstructured grid methodology, are performed for a proposed High Speed Civil Transport (HSCT) configuration, designated as the Reference H configuration within the High Speed Research (HSR) Program. The predicted results are correlated with appropriate experimental wind-tunnel data for the baseline configuration with and without control surface deflections for a range of angle of attack at M(sub infinity) = 0.95. Good correlations between the predictions and measured data have been obtained for the longitudinal aerodynamic characteristics of the baseline configuration. The incremental effects in the longitudinal aerodynamic characteristics due to horizontal rail deflections as well as wing leading-edge and trailing-edge flap deflections have also been predicted reasonably well. Computational results and correlations with data are also presented for the lateral and directional stability characteristics for a range of angle of attack at a constant sideslip angle as well as a range of sideslip angles at a constant angle of attack. In addition, the results are presented to assess the computational method performance and convergence characteristics.

Ghaffari, Farhad↗

DOE OSTI2022

Production of Fischer-Tropsch Synfuels at Nuclear Plants

A case study analysis was performed to evaluate nuclear-powered synthetic fuel production in the midwestern United States (U.S.). A Fischer-Tropsch (FT) fuel synthesis plant design was used as the basis for the analysis. The FT plant design was configured to produce a product slate consisting of diesel fuel, jet fuel, and motor gasoline blend stocks from carbon dioxide (CO 2 ) and hydrogen (H 2 ) feedstocks. The CO 2 feedstock for the FT plant was assumed to be sourced from biorefineries in the region around a Midwest light water reactor (LWR) nuclear power plant (NPP). The analysis specifies that power from the LWR is used to produce H 2 via high-temperature steam electrolysis and to operate the FT synfuel production plant. Capital costs were estimated for the FT plant while capital costs for the electrolysis plant were based on previous Idaho National Laboratory (INL) studies. In addition to labor and maintenance costs for the FT and electrolysis plants, operating costs also include the costs for CO 2 feedstock transport. An analysis was performed to determine the cost of transporting CO 2 from the distributed biorefinery sources to the centralized fuel synthesis plant as a function of the synfuel plant capacity and corresponding CO 2 demand. The primary revenue streams are associated with sales of the synthetic fuel products. The synthetic fuel products will likely follow the same market trends as the conventional fuel products. The synfuel price data was thus based on projections made by the U.S. Energy Information Administration (EIA) 2021 Annual Energy Outlook (AEO) for conventional fuel products minus federal and state taxes, as well as marketing and distribution costs. The economic analysis also considered cases that included and excluded revenues from the 2022 Inflation Reduction Act (IRA) clean hydrogen production tax credit (PTC) of $\$ $3.00/kg for the first ten years of operation. The economic analysis calculated the net present value (NPV) for cases involving steady-state synfuel production for comparison with the NPV for a business-as-usual case in which NPP continues to sell only electric power to the grid. A synfuel production “Reference Case” was considered in addition to sensitivity cases in which the plant capacity, electricity price, and synthetic fuel product prices were perturbed. The synfuel production Reference Case considered a scenario in which the electrolysis and synfuel plants utilized a combined electrical load of 1000 megawatt electrical (MWe) from the LWR with the balance of the LWR power output being sold to the electric grid. The economic analysis suggests that the synfuel production Reference Case evaluated in this analysis would lead to considerable economic potential for near-term deployment of a nuclear-based synfuel production plant. Specifically, the economic analysis suggests that the deployment of a 1000 megawatt (MW) nuclear-powered synfuel plant could result in a NPV increase of approximately $\$ $1.7 billion for a case with no clean synfuel price premium relative to conventional petroleum fuels when accounting for the additional revenues from the 2022 IRA clean hydrogen PTCs of $\$ $3/kg. Sensitivity analysis was performed to evaluate the effect of perturbation of selected model input parameters on the NPV for the synfuel production Reference Case. The sensitivity analysis indicates that the plant capacity has the largest impact on the differential NPV, with a smaller synfuel production capacity resulting in a decrease in revenue when a larger fraction of the power from the NPP is sold to the grid and a smaller fraction of the power is used to produce synthetic fuel products. The synfuel product pricing has the next largest impact on the differential NPV, with lower synfuel prices resulting in decreased NPV from decreased synfuel sales revenue while higher synfuel prices result in increased NPV from increased synfuel sales revenue. Electricity pricing has a smaller effect on the NPV than the fuel sales price since, in the Reference Case, most of the energy from the NPP is used for synfuel production and a smaller amount of the system revenues are associated with electrical power sales. However, the electricity price sensitivity does indicate that the Synfuel Integrated Energy System (IES) would have a greater NPV than the business-as-usual case (e.g., grid power sales only) when electricity market prices are low, suggesting that synfuel production could provide a strategy for decreasing the economic risks to NPPs posed by a loss of revenues attributed to falling electricity market prices.

10 SYNTHETIC FUELS↗

NASA NTRS2005

Topography Analysis and Visualization Software Supports a Guided Comparative Planetology Education Exhibit at the Smithsonian's Air and Space Museum

The Planetary Geodynamics Laboratory (http://geodynamics.gsfc.nasa.gov) of NASA s Goddard Space Flight Center designed, produced and recently delivered a "museum-friendly" version of GRIDVIEW, a grid visualization and analysis application, to the Smithsonian's National Air and Space Museum where it will be used in a guided comparative planetology education exhibit. The software was designed to enable museum visitors to interact with the same Earth and Mars topographic data and tools typically used by planetary scientists, and experience the thrill of discovery while learning about the geologic differences between Earth and Mars.

Roark, J. H.↗

DOE OSTI2016

A Systems Approach to Analyzing Cyber-Physical Threats in the Smart Grid

This paper presents a systems analysis approach to characterizing the risk of a Smart Grid to a load-drop attack. A characterization of the risk is necessary for the design of detection and remediation strategies to address the consequences of such attacks. Using concepts from systems health management and system engineering, this work (a) first identifies metrics that can be used to generate constraints for security features, and (b) lays out an end-to-end integrated methodology using separate network and power simulations to assess system risk. We demonstrate our approach by performing a systems-style analysis of a load-drop attack implemented over the AMI subsystem and targeted at destabilizing the underlying power grid.

Almajali, Anas↗

DOE OSTI2017

Resilience Metrics for the Electric Power System: A Performance-Based Approach.

Grid resilience is a concept related to a power system's ability to continue operating and delivering power even in the event that low probability, high-consequence disruptions such as hurricanes, earthquakes, and cyber-attacks occur. Grid resilience objectives focus on managing and, ideally, minimizing potential consequences that occur as a result of these disruptions. Currently, no formal grid resilience definitions, metrics, or analysis methods have been universally accepted. This document describes an effort to develop and describe grid resilience metrics and analysis methods. The metrics and methods described herein extend upon the Resilience Analysis Process (RAP) developed by Watson et al. for the 2015 Quadrennial Energy Review. The extension allows for both outputs from system models and for historical data to serve as the basis for creating grid resilience metrics and informing grid resilience planning and response decision-making. This document describes the grid resilience metrics and analysis methods. Demonstration of the metrics and methods is shown through a set of illustrative use cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1994

On the vortical-flow-prediction capability of an unstructured-grid Euler solver

The results from a concentrated computational effort are presented with the primary objective being directed at evaluating the vortical-flow-prediction capability of an unstructured-grid Euler solver. Both viscous and inviscid solutions, obtained from an established structured-grid method, along with experimental wind-tunnel data are used as benchmark measures to assess the validity of the unstructured-grid Euler results. Viscous effects on vortical flows are first identified by comparing the viscous and inviscid solutions obtained from the structured-grid method. Computational data analysis is then presented which reveals excellent correlations between the inviscid structured and unstructured-grid results in terms of off-surface flow structures, surface pressure distribution, and the predicted longitudinal aerodynamic characteristics. The sensitivity of the unstructured-grid inviscid solutions to grid refinement is also discussed along with an analysis of the convergence and performance characteristics for each method.

Unstructured grid↗

NASA NTRS1994

On the Vortical-Flow Prediction Capability of an Unstructured-Grid Euler Solver

The results from a concentrated computational effort are presented with the primary objective being directed at evaluating the vortical-flow-prediction capability of an unstructured-grid Euler solver. Both viscous and inviscid solutions, obtained from an established structured-grid method, along with an experimental wind-tunnel data are used as bench-mark measures to assess the validity of the unstructured-grid Euler results. Viscous effects on vortical flows are first identified by comparing the viscous and inviscid solutions obtained form the structured-grid method. Computational data analysis are then presented which reveal excellent correlations between the inviscid structured and unstructured-grid results in terms of off-surface flow structures, surface pressure distribution and the predicted longitudinal aerodynamic characteristics. The sensitivity of the unstructured-grid inviscid solutions to grid refinement is also discussed along with an analysis of the convergence and performance characteristics for each method.

Unstructured grid↗

DOE OSTI2021

Impact of Increased Inverter-Based Resources on Power System Small-Signal Stability

The transformation of the power system to include more distributed energy resources (DER) implies an increase in the number of inverter-based resources deployed on the grid. Envisioning future scenarios, this paper presents a small-signal stability analysis for a power grid comprising synchronous generators and inverter-based resources. Three types of inverter control are considered: grid following, droop-controlled grid forming, and virtual oscillator control grid forming. Although small-signal stability of power systems is a widely studied topic, systematic analysis of mixed machine-inverter systems with detailed control models at various inverter levels are limited. This paper addresses the gap with numerical simulations tailored to the IEEE 39-bus system. Results show the system may become unstable at high inverter level of grid-following inverters, and grid-forming inverter control can potentially improve system stability, thereby enabling very high level of DERs.

grid-following inverter↗

DOE OSTI2021

Impact of Increased Inverter Penetration on Power System Small-Signal Stability: Preprint

The transformation of the power system to include more distributed energy resources (DER) implies an increase in the number of inverter-based resources deployed on the grid. Envisioning future scenarios, this paper presents a small-signal stability analysis for a power grid comprising synchronous generators and inverter-based resources. Three types of inverter control are considered: grid following, droop-controlled grid forming, and virtual oscillator control grid forming. Although small-signal stability of power systems is a widely studied topic, systematic analysis of mixed machine-inverter systems with detailed control models at various inverter penetration levels are limited. This paper addresses the gap with numerical simulations tailored to the IEEE 39-bus system. Results show the system may become unstable at high inverter penetration level of grid-following inverters, and grid-forming inverter control can potentially improve system stability, thereby enabling very high level of DERs.

41 EE - Solar Energy Technologies Office (EE-4S)↗

NASA NTRS2000

Wavelet-Based Interpolation and Representation of Non-Uniformly Sampled Spacecraft Mission Data

A well-documented problem in the analysis of data collected by spacecraft instruments is the need for an accurate, efficient representation of the data set. The data may suffer from several problems, including additive noise, data dropouts, an irregularly-spaced sampling grid, and time-delayed sampling. These data irregularities render most traditional signal processing techniques unusable, and thus the data must be interpolated onto an even grid before scientific analysis techniques can be applied. In addition, the extremely large volume of data collected by scientific instrumentation presents many challenging problems in the area of compression, visualization, and analysis. Therefore, a representation of the data is needed which provides a structure which is conducive to these applications. Wavelet representations of data have already been shown to possess excellent characteristics for compression, data analysis, and imaging. The main goal of this project is to develop a new adaptive filtering algorithm for image restoration and compression. The algorithm should have low computational complexity and a fast convergence rate. This will make the algorithm suitable for real-time applications. The algorithm should be able to remove additive noise and reconstruct lost data samples from images.

Bose, Tamal↗

DOE OSTI2024

An Integrated Assessment of a G3 GMD Event on Large-Scale Power Grids: From Magnetometer Data to Geomagnetically Induced Current Analysis

Solar activities can cause geomagnetic disturbances (GMDs) that give rise to geomagnetically induced currents (GICs) which may compromise the reliability of the power system. In order to build more reliable models representing GMD interactions with the power grid, the power system’s detailed electrical model must be considered along with fluctuations in the earth’s magnetic and induced surface electric fields. Here, this study investigates the impact of incorporating spatially varying magnetic fields into surface electric field models on GMD risk metrics. A spatially independent magnetic field model and a spatially varying model are compared through simulations. To perform this analysis, the earth’s magnetic field disturbances are transformed into surface electric fields using respective one-dimensional earth conductivity models. Then, the modeling impact of these electric fields is studied using a 2,000-bus grid for Texas and a 25,000-bus grid for the northeast and mid- Atlantic regions of the United States. Simulation results reveal that the inclusion of spatially varying magnetic fields results in considerable differences in GMD risk metrics, highlighting the importance of accounting for spatial variability when assessing GMD risks in the power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1988

A simplified analysis of the multigrid V-cycle as a fast elliptic solver

For special model problems, Fourier analysis gives exact convergence rates for the two-grid multigrid cycle and, for more general problems, provides estimates of the two-grid convergence rates via local mode analysis. A method is presented for obtaining mutigrid convergence rate estimates for cycles involving more than two grids (using essentially the same analysis as for the two-grid cycle). For the simple cast of the V-cycle used as a fast Laplace solver on the unit square, the k-grid convergence rate bounds obtained by this method are sharper than the bounds predicted by the variational theory. Both theoretical justification and experimental evidence are presented.

Decker, Naomi H.↗

DOE OSTI2025

Guidance for Grid Resilience Decisions in Rural Minnesota

This report assesses the hazard landscape of the state of Minnesota, identifies weather hazards that are most impactful to the distribution system, includes a statewide assessment of household access to services dependent on reliable power, reviews resilience planning activities of electric utilities in Minnesota, and presents analysis of distribution grid performance in the face of extreme weather events with data from seven electric cooperatives dispersed throughout outstate Minnesota. This information is synthesized to provide considerations for resilience investment prioritization.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

A non-linear k-{epsilon} turbulent model sensitivity analysis for flow across a PWR spacer grid with mixing vanes

In this work we studied the sensitivity of different computational fluid dynamics (CFD) numerical solutions on turbulence model, domain discretization mesh type, and inlet boundary conditions. The case under examination is a turbulent one-phase flow (water) through a scaled nuclear pressurized water reactor (PWR) fuel assembly. The main feature of this geometrical configuration is the presence of a spacer grid with mixing vanes. The design of a spacer grid with mixing vanes plays a key role for the core heat transfer efficiency, increasing the coolant heat transfer coefficient. The main reason for this is the introduction of the top mixing vanes, which consist of an ordered repetitive succession of wings that generate secondary swirling flows. The increase of heat transfer efficiency also increases the critical heat flux (CHF), making it possible to increase the design and operational limits, far from boiling crises (departure of nucleate boiling in case of a PWR). The main focus of this work was to analyze the simulation capabilities of Reynolds-averaged Navier-Stokes (RANS) models (a cubic non-linear k-epsilon model formulation) for this complex flow geometry. The CFD code used was CD-Adapco STAR-CCM+.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

DISTINCT: Diversity in Solar Talent Through INnovative Curriculum and Training: An Integrated Research and Education Approach towards Creating Diversity and Advancing Utility-Scale Solar Technology

The DISTINCT project research objective is to develop an innovative N-port power converter for a utility-scale PV system that is modular, compact and cost-effective and that will enable the integration of a high-frequency, high-voltage solid-state transformer. The novelty of the proposed research is the electrical power conversion architecture using an N-port converter system that replaces the output 60Hz transformer with an integrated high-frequency low-weight solid-state transformer reducing power electronics and BOS costs to meet SunShot goals through modularity and direct high-voltage interconnection. A challenge in direct integration with a 13.8kV line is the high voltage handling capacity of the converters combined with high efficiency operation. The front-end converter for each port is a Neutral-Point Clamped (NPC) Multi-Level dc-dc Dual-Active Bridge (ML-DAB) which allows Maximum Power Point Tracking (MPPT). The integrated high frequency transformer provides the galvanic isolation between the PV and grid side and also steps up the low dc voltage from PV source. Following the ML-DAB stage, in each port, is an inverter with H-bridge configuration or NPC configuration. N number of NPC inverters’ outputs are cascaded to attain the per-phase line-to-neutral voltage to connect directly to the distribution grid (i.e. 13.8 kV). The cascaded inverters have the inherent advantage of using lower rated devices, smaller filters and low Total Harmonic Distortion (THD) required for PV grid interconnection. Our analysis and simulation results show improved performance on cost, efficiency, service life with zero downtime and THD. A comprehensive control scheme is presented to ensure the maximum power from each port and each phase are sent to the grid. A functional prototype of a 2-port converter with ML-DAB and cascaded H-bridges has been designed, built, and tested in a laboratory setup to verify the target technical metrics. The N-port converter system due to its modular structure with individual control per port can be easily adapted to integrate functionalities that go well beyond the conventional grid support functions and mitigates impacts of forecasted fast ramp downs or ramp ups and single-fault conditions by automatic reconfiguration of the output.

14 SOLAR ENERGY↗

DOE OSTI2024

Pumped Storage Hydropower Potential and Opportunities

Pumped storage hydropower (PSH) is a flexible energy storage technology with the potential to improve grid reliability, resiliency, and stability in the electric grid of the future. NREL has developed a range of data and tools to help understand opportunities for new PSH deployment, including nationwide resource assessment data, a bottom-up component-level cost model, and a lifecycle greenhouse gas emissions calculator. These datasets can then be used to inform grid planning models, analysis, and decision making to understand the role PSH can play in the power sector.

cost↗